Methods and apparatus for de-artifact filtering using multi-lattice sparsity-based filtering

Abstract

Methods and apparatus are provided for de-artifact filtering using multi-lattice sparsity-based filtering. The apparatus includes a sparsity-based filter ( 600 ) for de-artifact filtering picture data for a picture. The picture data includes different sub-lattice samplings of the picture. Sparsity-based filtering thresholds for the filter are varied temporally.

1 . An apparatus, comprising:
 a sparsity-based filter for de-artifact filtering picture data for a picture, the picture data including different sub-lattice samplings of the picture, wherein sparsity-based filtering thresholds for the filter are varied temporally.   
     
     
         2 . The apparatus of  claim 1 , wherein the sparsity-based filtering thresholds are varied spatially. 
     
     
         3 . The apparatus of  claim 2 , wherein the sparsity based filtering thresholds are varied responsive to at least one of local signal statistics, global signal statistics, local noise, global noise, local distortion, global distortion, compression parameters, prediction modes, a user selection, a video quality measure, and a coding cost measure. 
     
     
         4 . The apparatus of  claim 1 , where a class map corresponding to a plurality of classes is created and a respective threshold is selected for each of the plurality of classes, wherein each of the plurality of classes corresponds to a particular set of coding conditions. 
     
     
         5 . The apparatus of  claim 1 , wherein the sparsity-based filtering thresholds are encoded using at least one of uniform coded values, differentially coded values with respect to previous threshold values, and an average threshold value, wherein the average threshold value is dependent on at least one of at least one coding setting, at least one coding profile, and at least one quantization parameter, and wherein at least one of the uniform coded values and the differential values are encoded using at least one of uniform codes, variable length codes and arithmetic codes. 
     
     
         6 . The apparatus of  claim 1 , wherein filtering threshold information is transmitted in a coded video bit-stream using at least one high level syntax element. 
     
     
         7 . The apparatus of  claim 1 , wherein said sparsity-based filter is configured for at least one of in-loop processing and out-loop processing of the picture data. 
     
     
         8 . The apparatus of  claim 1 , wherein said sparsity-based filter is comprised in at least one of a video encoder and a video decoder. 
     
     
         9 . The apparatus of  claim 1 , wherein the sparsity-based filtering thresholds are selectively applied to an entirety of a picture corresponding to the picture data or a portion thereof. 
     
     
         10 . The apparatus of  claim 9 , wherein the sparsity-based filtering thresholds are independently or jointly adapted. 
     
     
         11 . The apparatus of  claim 1 , wherein sparsity-based filtering operations performed by said sparsity-based filter are capable of being at least one of combined, adapted, enabled, and disabled. 
     
     
         12 . The apparatus of  claim 11 , wherein said sparsity-based filter is comprised in a video encoder, and whether any of the de-artifacting operations are at least one of combined, adapted, enabled, and disabled is signaled to a corresponding decoder using at least one high level syntax element. 
     
     
         13 . The apparatus of  claim 11 , wherein said sparsity-based filter is comprised in a video decoder, and whether any of the de-artifacting operations are at least one of combined, adapted, enabled, and disabled is determined from at least one high level syntax element. 
     
     
         14 . A method, comprising:
 de-artifact filtering picture data for a picture, the picture data including different sub-lattice samplings of the picture, wherein sparsity-based filtering thresholds for the filtering are varied temporally.   
     
     
         15 . The method of  claim 14 , wherein the sparsity-based filtering thresholds are varied spatially. 
     
     
         16 . The method of  claim 15 , wherein the sparsity based filtering thresholds are varied responsive to at least one of local signal statistics, global signal statistics, local noise, global noise, local distortion, global distortion, compression parameters, prediction modes, a user selection, a video quality measure, and a coding cost measure. 
     
     
         17 . The method of  claim 14 , further comprising:
 creating a class map corresponding to a plurality of classes; and   selecting a respective threshold for each of the plurality of classes, wherein each of the plurality of classes corresponds to a particular set of encoding conditions.   
     
     
         18 . The method of  claim 14 , further comprising encoding the sparsity-based filtering thresholds using at least one of uniform coded values, differentially coded values with respect to previous threshold values, and an average threshold value, wherein the average threshold value is dependent on at least one of at least one coding setting, at least one encoding profile, and at least one quantization parameter, and wherein at least one of the uniform coded values and the differential values are encoded using at least one of uniform codes, variable length codes and arithmetic codes. 
     
     
         19 . The method of  claim 14 , further comprising transmitting filtering threshold information in a coded video bit-stream using at least one high level syntax element. 
     
     
         20 . The method of  claim 14 , further comprising configuring the sparsity-based filtering for at least one of in-loop processing and out-loop processing of the picture data. 
     
     
         21 . The method of  claim 14 , wherein the sparsity-based filtering is performed in at least one of a video encoder and a video decoder. 
     
     
         22 . The method of  claim 14 , wherein the sparsity-based filtering thresholds are selectively applied to an entirety of a picture corresponding to the picture data or a portion thereof. 
     
     
         23 . The method of  claim 22 , wherein the sparsity-based filtering thresholds are independently or jointly adapted. 
     
     
         24 . The method of  claim 14 , wherein said sparsity-based filtering step comprises applying at least one sparsity-based filtering operation to the picture data, wherein the at least one sparsity-based filtering operation is capable of being at least one of combined, adapted, enabled, and disabled. 
     
     
         25 . The method of  claim 24 , wherein the sparsity-based filtering is performed in a video encoder, and the method further comprises signaling, to a corresponding decoder, whether any of the de-artifacting operations are at least one of combined, adapted, enabled, and disabled using at least one high level syntax element. 
     
     
         26 . The method of  claim 24 , wherein the sparsity-based filtering is performed in a video decoder, and the method further comprises determining whether any of the de-artifacting operations are at least one of combined, adapted, enabled, and disabled from at least one high level syntax element.